E2B
Open-source runtime enabling secure, scalable code execution in isolated cloud sandboxes for AI applications.
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Product Overview
What is E2B?
E2B provides developers with a robust open-source infrastructure to execute code in secure, isolated cloud environments. Designed for agentic and AI-driven applications, it allows each AI agent or user session to run code in its own lightweight virtual machine, supporting complex workflows and untrusted code execution. E2B supports rapid sandbox startup, seamless integration with popular LLMs, and offers SDKs for both Python and JavaScript. Its architecture simplifies infrastructure management, enhances security, and scales to meet demanding workloads.
Key Features
Isolated Cloud Sandboxes
Each user or AI agent operates within a secure, isolated virtual machine, ensuring safe execution of code and preventing cross-session interference.
Rapid Startup and Scalability
Sandboxes can be provisioned in under 200ms, enabling high concurrency and responsiveness for real-time applications.
LLM-Agnostic Integration
Compatible with any large language model, including OpenAI, Llama, Anthropic, and custom models, providing flexibility for diverse AI workflows.
Comprehensive SDK Support
Offers Python and JavaScript/TypeScript SDKs for easy integration, enabling control over sandbox lifecycle, filesystem, and process management.
Persistent and Long-Running Sessions
Supports sandbox sessions lasting up to 24 hours, with features for pausing, resuming, and maintaining workflow state.
Self-Hosting and Cloud Deployment
Can be deployed on major cloud providers or self-hosted, giving teams full control over infrastructure and data.
Use Cases
- AI Coding Assistants : Power code interpreters, copilots, and autonomous agents that require secure, isolated environments for code execution.
- Data Analysis and Visualization : Enable AI-driven data analysis, charting, and visualization by running scripts and generating outputs in a controlled sandbox.
- Automated Testing and Evaluation : Run codegen evaluations, automated tests, or benchmarks for AI-generated code in reproducible and isolated environments.
- Custom App Backends : Serve as the execution layer for AI-powered applications needing dynamic code execution, package installation, or file management.
- Educational Coding Platforms : Provide students and educators with safe, disposable coding environments for learning and experimentation.
FAQs
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